Mainak Jas
- Cognitive Neuroscience top 2%
- Neural dynamics and brain function 8
- Functional Brain Connectivity Studies 8
- EEG and Brain-Computer Interfaces 7
- Visual perception and processing mechanisms 2
- Signal Processing top 10%
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- Advanced MRI Techniques and Applications 4
- Radiomics and Machine Learning in Medical Imaging 2
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- AI in cancer detection 3
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- Medical Image Segmentation Techniques 2
- Co-authors
- Alexandre GramfortDenis A. EngemannYousra BekhtiFederico RaimondoMatti HämäläinenEric B. LarsonLauri ParkkonenPavan Ramkumar
- Partner nations
- United StatesFranceFinland
In The Last Decade
Mainak Jas
18 papers receiving 796 citations
Hit Papers
Peers
Comparison fields: 5 of 83
- Cognitive Neuroscience 666
- Signal Processing 58
- Experimental and Cognitive Psychology 64
- Cellular and Molecular Neuroscience 69
- Computational Mathematics 2
Countries citing papers authored by Mainak Jas
This map shows the geographic impact of Mainak Jas's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mainak Jas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mainak Jas more than expected).
Fields of papers citing papers by Mainak Jas
This network shows the impact of papers produced by Mainak Jas. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mainak Jas. The network helps show where Mainak Jas may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mainak Jas, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 2 | |
| 3 | 2023 | 3 | |
| 4 | 2021 | 16 | |
| 5 | 2020 | 27 | |
| 6 | 2020 | 65 | |
| 7 | 2019 | 68 | |
| 8 | 2019 | 14 | |
| 9 | 2019 | 43 | |
| 10 | 2018 | 70 | |
| 11 | 2018 | 88 | |
| 12 | Autoreject: Automated artifact rejection for MEG and EEG databreakdown → | 2017 | 311 |
| 13 | 2016 | 1 | |
| 14 | Image specificity | 2015 | 12 |
| 15 | 2015 | 10 | |
| 16 | 2014 | 1 | |
| 17 | 2013 | 15 | |
| 18 | 2013 | 55 | |
| 19 | 2012 | 1 |
About Mainak Jas
Mainak Jas is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Signal Processing, having authored 19 papers that have together received 802 indexed citations. Recurring topics across this work include Neural dynamics and brain function (8 papers), Functional Brain Connectivity Studies (8 papers), EEG and Brain-Computer Interfaces (7 papers), Advanced MRI Techniques and Applications (4 papers), AI in cancer detection (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Visual perception and processing mechanisms (2 papers) and Medical Image Segmentation Techniques (2 papers). The work is most often cited by research in Cognitive Neuroscience (666 citations), Signal Processing (58 citations), Experimental and Cognitive Psychology (64 citations), Cellular and Molecular Neuroscience (69 citations) and Computational Mathematics (2 citations). Mainak Jas has collaborated with scholars based in United States, France and Finland. Frequent co-authors include Alexandre Gramfort, Denis A. Engemann, Yousra Bekhti, Federico Raimondo, Matti Hämäläinen, Eric B. Larson, Lauri Parkkonen, Pavan Ramkumar, Sebastian Pannasch and Riitta Hari. Their work appears in journals such as Journal of Neuroscience, NeuroImage, Scientific Reports, Journal of Digital Imaging and Cell Reports.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.